Six areas of work. Each one lists what it includes, what you actually receive, and the tools we use—so you can judge fit before a call rather than after one.
The full arc from a rough product decision to a running system. Architecture, application code, quality, deployment, and the changes after launch.
Software that people use for hours, not minutes. Multi-tenant products, operational platforms, internal tools, and customer-facing portals.
Retrieval and document systems, assistants, and automation that process work with confidence. AI features must demonstrably remove work.
Design for software that people use for real work. Flows, systems, and design systems rather than marketing layouts.
The unglamorous work that decides whether shipping is routine or frightening: environments, releases, monitoring, ownership, and rollback.
Gluing systems to each other. Data models that hold up to schema changes and integrations with the tools the business already depends on.
Plenty of AI features are slower, more expensive, and less accurate than the boring alternative. Before we build one, we define the simple version, check the numbers, and build the intelligent version only if it wins.
Discuss an AI use case →
pipeline.config.yaml
# The pipeline circuit schema: AI
model:
provider: "internal_at_a_fixed_system_call"
item: "lookup at a fixed system call"
fallback:
human_review: required
guardrails:
max_confidence: 0.92
human_in_the_loop: trueWe keep a deliberately conventional stack. Boring technology is easier to hire for, easier to operate, and less likely to become your problem two years from now.
We will recommend the one that fits, including when that recommendation is the wrong one for us. Pricing is quoted after scope is clear, never before.
A specific outcome with an agreed scope, requirements that are reasonably clear, and a delivery plan you can judge in advance.
A monthly engagement where we act as your senior engineering team, matched with yours and learning the work as your own team does.
Monitoring, improvement updates, and maintenance on an ongoing basis—without a large internal team required to run it.